Today, models are primarily trained on the publicly scraped internet. What if 100M users contributed their private data from siloed platforms to create a user-owned foundation model?
Most of the TEE controversy assumes that TEEs are going to be used to replace zk or a blockchain, rather than complement them
A well-designed system (like
@withvana
) uses both crypto consensus where you don't trust hardware, and TEEs for privacy-specific applications
@0xfoobar
Exactly what you rely on the TEE for depends on how you structure the application.
In your example, eg require an zk proof for correctness and rely on TEE only for privacy.
Basically in protocol design you should limit scope of dependencies, and favor simplicity + lindyness
Open sourcing a community-led market map of Decentralized AI.
Most market maps are static and biased. We wanted to make one that was interactive and crowdsourced.
Pls submit any projects that are missing.
We implemented a 3d viz using
@d3js_org
and a
Usually, AI models are created and owned by a single company using public data.
@rdatadao
's AI model is created and owned by a collective of 140k users who contributed their private data.
User-owned data -> user-owned AI
Through a collaboration with
@oraprotocol
we’re helping
@rdatadao
turn their data into an on-chain AI for shitposting. 😳😂💩
This will be the first user-owned model trained on user-owned data.
The DAO plans to develop their early prototype () and launch
A great start to EthCC at Open Source AI day, hosted by
@ekang426
!
I talked about user-owned foundation models and non-custodial data
@withvana
Incredible to see hundreds of people gathered to build towards user-owned AI. Also, enjoyed the mini
@ZuBerlinCity
reunion :)
The current bottleneck in AI has shifted from compute to data. How do we overcome the great data wall?
Satori Testnet is a step towards data abundance, pushing the frontiers of user-owned AI. It is designed to liberate data from walled gardens
At EthCC all week, it's crazy how many decentralized AI events there are! It was a little known category just a year ago. Find me throughout the week talking about user-owned AI
The more context an LLM has on you, the more helpful it is. But the cross-platform data (WhatsApp, iMessage, gmail) is stuck in walled gardens
@withvana
makes data portable, even from web2 walled gardens. Login w wallet -> all your data is there, just like your funds
Proof of work was great bc you could become an owner in the network w just an old computer. Proof of stake networks compound existing ownership.. hard to bring new people in that way
Proof of contribution
@withvana
lets you earn ownership in the network with just your data
we need less tokens that people can just buy and we need more tokens that people have to work for/earn
in some sense, mining was a form of earning, but we need to evolve further and bring that into a more accessible vehicle for the masses; but also one that’s less passive.
It’s becoming so much easier (and more fun!) to build onchain. Many projects that make the user-owned internet easier to interact with have been heads-down building throughout the bear market.
Foundation models tend towards monopolies, but that's not the only option. We as users should create our own best foundation model — we have the data and compute to make it possible. Detailed post:
The data wall is one of the main barriers of AI progress.
Current approaches: scrape the internet, buy data ($20-$200/response), license it from companies
@withvana
's solution: give users true ownership in the AI models their data helps train
Multi-turn data is incredibly expensive today. Single answers go for $20-$200 depending on quality.
Assuming markets are somewhat efficient, this is a reasonable proxy for the atomic costs to aggregate "new data" for LLMs.
Given (a) we've exhausted a non-trivial fraction of
Foundation models require a lot of compute, but users have a lot of that too. Ethereum miners’ combined compute is 50 times greater than that used to train leading foundation models.
A data DAO has two main components: 1) onchain governance, with tokens earned for data contributions, and 2) a secure server, with a public-private key pair for encryption, where the community-owned dataset resides.
The true promise of crypto is digital sovereignty: own not just your funds, but your data. Make data non-custodial and private
This is what
@withvana
is designed for - the first l1 for user-owned data. Fulfilling what got many of us into crypto in the first place
Leading AI models only work because they are trained on your data (without your permission). Shouldn't you own a piece of the AI models that your data helps create?
r/datadao allows users to pool and govern their data, rewarding contributors with a dataset-specific token that represents ownership of the particular dataset. It’s a bit like a labor union for data.
Exciting to see the progress that data DAOs on Satori testnet are making. Many of the builders are early bittensor subnet creators or miners competing for one of the 16 spots on Vana - a really strong group of developers
Today, the 100th data DAO was deployed to Satori testnet. These data DAOs each implement a data liquidity pool (a new cryptoeconomic primitive) for a specific user-owned dataset, and advance the path towards a user-owned AI foundation model.
Decentralized AI is accelerating :)
Great to learn more about
@DlpLabs
building out data DAOs on
@withvana
- Starting with resume data from LinkedIn
- Focused on data licensing and already has a data buyer
- Highlighted just how valuable LinkedIn data is, which they used to sell while working at LinkedIn
Reddit was one of the last web2 products that still felt community owned. Leading up to their IPO, incentives have shifted. The extract cycle of web2 risks ruining products we love
Let's create a new, user-owned reddit:
Does anyone else find it wild that Reddit sells YOUR data for millions of dollars and you have zero upside or ownership?
The world is lucky to have the brilliant
@anna_kazlauskas
persistently working to make collectively owned data a reality.
The current path of society is to allow big tech to take our data and use it to train AI models that do our jobs. The only way to prevent this is through collective action. Data is currency, and collective data is power.
Congrats to
@ErikVoorhees
on the launch of
@TryVenice
. It strikes a balance for privacy-focused users who want convenience: it obfuscates data by mixing llm requests, similar to a crypto mixer, then just stores history encrypted in your browser
This private data is valuable, as we've seen in recent deals like Google paying Reddit $60M a year for training data. And users have a lot of it: 100x more than the data used to train leading foundation models.
On the increasing value of data in an AI-first world
"So does AI change how much my data is worth? In isolation, probably not. But collectively? The value is there."
AI is reshaping the data economy, but individual datasets remain undervalued. The real potential lies in data collectives, where users pool resources + own a stake in the value their data creates.
As we start to rely on AI models more and more, they become our source of truth. We shouldn't let a single company control that truth. Google's AI is a recent example of this - do you want extreme wokeness to rewrite history?
AI should be owned and controlled by users.
✨ZuBerlin is much more than just crypto! It's all about integrating various fields of cutting-edge technology, such as AI, and bringing diverse people together. 👥
We're super excited to have
@anna_kazlauskas
, founder of
@withvana
, with us! She’s part of curating an exceptional
Great summary of the race for private data
"Few platforms with abundant data accumulated organically over the years haven’t signed agreements with generative AI developers, it seems — from Photobucket to Tumblr to Q&A site Stack Overflow."
Building this
@withvana
, using proof of contribution to measure how original the training data is. Data contributors get paid based on how much the AI model they created from their data is used
Training data startup idea:
- ask users to submit extremely original training data. Extremely original ≈ no known LLM can complete a substring.
- sell the data to AI model companies for the user. If the user's data is incorporated in a model (it can now complete a substring),
Feels wrong when AI is taught based on your content and you don't own it
Has economic implications too -> if someone built an AI
@MKBHD
trained on his data, shouldn't he be the one to own it and earn from it?
Apple has sourced data for their AI from several companies
One of them scraped tons of data/transcripts from YouTube videos, including mine
Apple technically avoids "fault" here because they're not the ones scraping
But this is going to be an evolving problem for a long time
I love seeing their dedication start to enable real products that shift power back towards the individual. Some of the amazing projects that came together to make
@rdatadao
possible:
Apple published a full 2.5T token open source dataset
This is rare - usually companies just publish AI model weights, not the underlying dataset (privacy/ownership/IP issues)
Fun dataset to play with over the weekend
A big question in decentralized AI is distributed training. Token incentives can aggregate GPUs, but can those distributed GPUs work for foundation model training?
Last week at
@ZuBerlinCity
,
@flwrlabs
presented a 1.3B param LLM trained in a fully federated way
Vana runs on proof-of-contribution, which rewards data contributors based on their data teaches an AI model
Measuring and incentivizing data quality is hard, but is key to a user-owned foundation model
The AI world needs data, but public scraping without the consent of data owners is not the answer
@kwiens
should own the AI models their content helps train, not the company that decided to scrape it
Hey
@AnthropicAI
: I get you're hungry for data. Claude is really smart! But do you really need to hit our servers a million times in 24 hours?
You're not only taking our content without paying, you're tying up our devops resources. Not cool.
@KyleSamani
> You can only own things that are naturally exclusionary
Agreed, this is a "double spend problem for data"
Data markets don't work unless you can exclude access to it, since why pay for something that you can just get for free
Data is not exclusionary today but can be
@tommyeastman21
@withvana
is building the data piece. Decentralized data contributions help overcome the data wall, which is the bottleneck in AI today
@JonasWustrack
@realGeorgeHotz
@yacineMTB
In the data case, decentralization has an advantage through data regulation, which ensures users can always export their data
A centralized player can’t get access to Instagram, Reddit, X, Discord, YouTube since they’d get blocked or charged very high fees
@keoneHD
5) forces you to clearly articulate your thinking
6) opportunity for feedback from others as you write
7) shows evolution of your thinking overtime (eg I wrote a 2022 post on user-owned AI models, then an update in 2024)
8) allows people to discover you through your writing
@Tyler_Did_It
This is an amazing experiment
@rdatadao
you all could deploy the new AI shitposting model to see what happens when you set it free. Have it post autonomously and give it some tokens to get started
@srnlrsn
@0xDesigner
You actually legally own all your platform data bc of data regulation in the EU and California. You just grant a very permissive license to them to use it.
Strava, Chase, Reddit, Twitter, all the data you’ve created is legally (although not yet in practice) yours
@SahilLalani0
@withvana
Good question. Top of the list: iMessage data, Amazon purchase data, Google drive data, email data, Amazon Alexa data (audio), chatGPT exports. Rewind data would be good too
@artieart88
any other sources to add from what you’ve seen in data sales?
@0xDesigner
@withvana
Short answer: non-custodial data
Longer answer:
- Export your platform data, leveraging data regulation
- Encrypt your data w a key derived from your crypto wallet and store it w your storage provider of choice
- Login w your wallet and sign a tx granting access to the data the
@seppuku_you
@jbrukh
Exactly. If you put private data onchain, someone can just take a copy of it and then you've lost your data/privacy
None of the decentralized storage solutions work either as they're not GDPR compliant/designed for personal data
We built to solve this